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<title>OpenCV: Canny Edge Detector</title>
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<li class="navelem"><a class="el" href="../../d9/df8/tutorial_root.html">OpenCV Tutorials</a></li><li class="navelem"><a class="el" href="../../d7/da8/tutorial_table_of_content_imgproc.html">Image Processing (imgproc module)</a></li>  </ul>
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<div class="title">Canny Edge Detector </div>  </div>
</div><!--header-->
<div class="contents">
<div class="textblock"><p><b>Prev Tutorial:</b> <a class="el" href="../../d5/db5/tutorial_laplace_operator.html">Laplace Operator</a></p>
<p><b>Next Tutorial:</b> <a class="el" href="../../d9/db0/tutorial_hough_lines.html">Hough Line Transform</a></p>
<table class="doxtable">
<tr>
<th align="right"></th><th align="left"></th></tr>
<tr>
<td align="right">Original author </td><td align="left">Ana Huamán </td></tr>
<tr>
<td align="right">Compatibility </td><td align="left">OpenCV &gt;= 3.0 </td></tr>
</table>
<h2>Goal </h2>
<p>In this tutorial you will learn how to:</p>
<ul>
<li>Use the OpenCV function <a class="el" href="../../dd/d1a/group__imgproc__feature.html#ga04723e007ed888ddf11d9ba04e2232de">cv::Canny</a> to implement the Canny Edge Detector.</li>
</ul>
<h2>Theory </h2>
<p>The <em>Canny Edge detector</em> <a class="el" href="../../d0/de3/citelist.html#CITEREF_Canny86">[41]</a> was developed by John F. Canny in 1986. Also known to many as the <em>optimal detector</em>, the Canny algorithm aims to satisfy three main criteria:</p><ul>
<li><b>Low error rate:</b> Meaning a good detection of only existent edges.</li>
<li><b>Good localization:</b> The distance between edge pixels detected and real edge pixels have to be minimized.</li>
<li><b>Minimal response:</b> Only one detector response per edge.</li>
</ul>
<h3>Steps</h3>
<ol type="1">
<li><p class="startli">Filter out any noise. The Gaussian filter is used for this purpose. An example of a Gaussian kernel of \(size = 5\) that might be used is shown below:</p>
<p class="formulaDsp">
\[K = \dfrac{1}{159}\begin{bmatrix} 2 &amp; 4 &amp; 5 &amp; 4 &amp; 2 \\ 4 &amp; 9 &amp; 12 &amp; 9 &amp; 4 \\ 5 &amp; 12 &amp; 15 &amp; 12 &amp; 5 \\ 4 &amp; 9 &amp; 12 &amp; 9 &amp; 4 \\ 2 &amp; 4 &amp; 5 &amp; 4 &amp; 2 \end{bmatrix}\]
</p>
</li>
<li>Find the intensity gradient of the image. For this, we follow a procedure analogous to Sobel:<ol type="a">
<li>Apply a pair of convolution masks (in \(x\) and \(y\) directions: <p class="formulaDsp">
\[G_{x} = \begin{bmatrix} -1 &amp; 0 &amp; +1 \\ -2 &amp; 0 &amp; +2 \\ -1 &amp; 0 &amp; +1 \end{bmatrix}\]
</p>
 <p class="formulaDsp">
\[G_{y} = \begin{bmatrix} -1 &amp; -2 &amp; -1 \\ 0 &amp; 0 &amp; 0 \\ +1 &amp; +2 &amp; +1 \end{bmatrix}\]
</p>
</li>
<li>Find the gradient strength and direction with: <p class="formulaDsp">
\[\begin{array}{l} G = \sqrt{ G_{x}^{2} + G_{y}^{2} } \\ \theta = \arctan(\dfrac{ G_{y} }{ G_{x} }) \end{array}\]
</p>
 The direction is rounded to one of four possible angles (namely 0, 45, 90 or 135)</li>
</ol>
</li>
<li><em>Non-maximum</em> suppression is applied. This removes pixels that are not considered to be part of an edge. Hence, only thin lines (candidate edges) will remain.</li>
<li><p class="startli"><em>Hysteresis</em>: The final step. Canny does use two thresholds (upper and lower):</p><ol type="a">
<li>If a pixel gradient is higher than the <em>upper</em> threshold, the pixel is accepted as an edge</li>
<li>If a pixel gradient value is below the <em>lower</em> threshold, then it is rejected.</li>
<li>If the pixel gradient is between the two thresholds, then it will be accepted only if it is connected to a pixel that is above the <em>upper</em> threshold.</li>
</ol>
<p class="startli">Canny recommended a <em>upper</em>:<em>lower</em> ratio between 2:1 and 3:1.</p>
</li>
<li>For more details, you can always consult your favorite Computer Vision book.</li>
</ol>
<h2>Code </h2>
 <div class='newInnerHTML' title='cpp' style='display: none;'>C++</div><div class='toggleable_div label_cpp' style='display: none;'><ul>
<li>The tutorial code's is shown lines below. You can also download it from <a href="https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/ImgTrans/CannyDetector_Demo.cpp">here</a> <div class="fragment"><div class="line"></div><div class="line"><span class="preprocessor">#include &quot;<a class="code" href="../../d1/d4f/imgproc_2include_2opencv2_2imgproc_8hpp.html">opencv2/imgproc.hpp</a>&quot;</span></div><div class="line"><span class="preprocessor">#include &quot;<a class="code" href="../../d4/dd5/highgui_8hpp.html">opencv2/highgui.hpp</a>&quot;</span></div><div class="line"><span class="preprocessor">#include &lt;iostream&gt;</span></div><div class="line"></div><div class="line"><span class="keyword">using namespace </span><a class="code" href="../../d2/d75/namespacecv.html">cv</a>;</div><div class="line"></div><div class="line"><a class="code" href="../../d3/d63/classcv_1_1Mat.html">Mat</a> src, src_gray;</div><div class="line"><a class="code" href="../../d3/d63/classcv_1_1Mat.html">Mat</a> dst, detected_edges;</div><div class="line"></div><div class="line"><span class="keywordtype">int</span> lowThreshold = 0;</div><div class="line"><span class="keyword">const</span> <span class="keywordtype">int</span> max_lowThreshold = 100;</div><div class="line"><span class="keyword">const</span> <span class="keywordtype">int</span> ratio = 3;</div><div class="line"><span class="keyword">const</span> <span class="keywordtype">int</span> kernel_size = 3;</div><div class="line"><span class="keyword">const</span> <span class="keywordtype">char</span>* window_name = <span class="stringliteral">&quot;Edge Map&quot;</span>;</div><div class="line"></div><div class="line"><span class="keyword">static</span> <span class="keywordtype">void</span> CannyThreshold(<span class="keywordtype">int</span>, <span class="keywordtype">void</span>*)</div><div class="line">{</div><div class="line">    <a class="code" href="../../d4/d86/group__imgproc__filter.html#ga8c45db9afe636703801b0b2e440fce37">blur</a>( src_gray, detected_edges, <a class="code" href="../../dc/d84/group__core__basic.html#ga346f563897249351a34549137c8532a0">Size</a>(3,3) );</div><div class="line"></div><div class="line">    <a class="code" href="../../dd/d1a/group__imgproc__feature.html#ga04723e007ed888ddf11d9ba04e2232de">Canny</a>( detected_edges, detected_edges, lowThreshold, lowThreshold*ratio, kernel_size );</div><div class="line"></div><div class="line">    dst = <a class="code" href="../../d1/da0/classcv_1_1Scalar__.html#ac1509a4b8454fe7fe29db069e13a2e6f">Scalar::all</a>(0);</div><div class="line"></div><div class="line">    src.<a class="code" href="../../d3/d63/classcv_1_1Mat.html#a33fd5d125b4c302b0c9aa86980791a77">copyTo</a>( dst, detected_edges);</div><div class="line"></div><div class="line">    <a class="code" href="../../d7/dfc/group__highgui.html#ga453d42fe4cb60e5723281a89973ee563">imshow</a>( window_name, dst );</div><div class="line">}</div><div class="line"></div><div class="line"></div><div class="line"><span class="keywordtype">int</span> main( <span class="keywordtype">int</span> argc, <span class="keywordtype">char</span>** argv )</div><div class="line">{</div><div class="line">  <a class="code" href="../../d0/d2e/classcv_1_1CommandLineParser.html">CommandLineParser</a> parser( argc, argv, <span class="stringliteral">&quot;{@input | fruits.jpg | input image}&quot;</span> );</div><div class="line">  src = <a class="code" href="../../d4/da8/group__imgcodecs.html#ga288b8b3da0892bd651fce07b3bbd3a56">imread</a>( <a class="code" href="../../d6/dba/group__core__utils__samples.html#ga3a33b00033b46c698ff6340d95569c13">samples::findFile</a>( parser.get&lt;<a class="code" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a>&gt;( <span class="stringliteral">&quot;@input&quot;</span> ) ), <a class="code" href="../../d8/d6a/group__imgcodecs__flags.html#gga61d9b0126a3e57d9277ac48327799c80af660544735200cbe942eea09232eb822">IMREAD_COLOR</a> ); <span class="comment">// Load an image</span></div><div class="line"></div><div class="line">  <span class="keywordflow">if</span>( src.<a class="code" href="../../d3/d63/classcv_1_1Mat.html#abbec3525a852e77998aba034813fded4">empty</a>() )</div><div class="line">  {</div><div class="line">    std::cout &lt;&lt; <span class="stringliteral">&quot;Could not open or find the image!\n&quot;</span> &lt;&lt; std::endl;</div><div class="line">    std::cout &lt;&lt; <span class="stringliteral">&quot;Usage: &quot;</span> &lt;&lt; argv[0] &lt;&lt; <span class="stringliteral">&quot; &lt;Input image&gt;&quot;</span> &lt;&lt; std::endl;</div><div class="line">    <span class="keywordflow">return</span> -1;</div><div class="line">  }</div><div class="line"></div><div class="line">  dst.<a class="code" href="../../d3/d63/classcv_1_1Mat.html#a55ced2c8d844d683ea9a725c60037ad0">create</a>( src.<a class="code" href="../../d3/d63/classcv_1_1Mat.html#a146f8e8dda07d1365a575ab83d9828d1">size</a>(), src.<a class="code" href="../../d3/d63/classcv_1_1Mat.html#af2d2652e552d7de635988f18a84b53e5">type</a>() );</div><div class="line"></div><div class="line">  <a class="code" href="../../d8/d01/group__imgproc__color__conversions.html#ga397ae87e1288a81d2363b61574eb8cab">cvtColor</a>( src, src_gray, <a class="code" href="../../d8/d01/group__imgproc__color__conversions.html#gga4e0972be5de079fed4e3a10e24ef5ef0a353a4b8db9040165db4dacb5bcefb6ea">COLOR_BGR2GRAY</a> );</div><div class="line"></div><div class="line">  <a class="code" href="../../d7/dfc/group__highgui.html#ga5afdf8410934fd099df85c75b2e0888b">namedWindow</a>( window_name, <a class="code" href="../../d0/d90/group__highgui__window__flags.html#ggabf7d2c5625bc59ac130287f925557ac3acf621ace7a54954cbac01df27e47228f">WINDOW_AUTOSIZE</a> );</div><div class="line"></div><div class="line">  <a class="code" href="../../d7/dfc/group__highgui.html#gaf78d2155d30b728fc413803745b67a9b">createTrackbar</a>( <span class="stringliteral">&quot;Min Threshold:&quot;</span>, window_name, &amp;lowThreshold, max_lowThreshold, CannyThreshold );</div><div class="line"></div><div class="line">  CannyThreshold(0, 0);</div><div class="line"></div><div class="line">  <a class="code" href="../../d7/dfc/group__highgui.html#ga5628525ad33f52eab17feebcfba38bd7">waitKey</a>(0);</div><div class="line"></div><div class="line">  <span class="keywordflow">return</span> 0;</div><div class="line">}</div></div><!-- fragment -->  </div> </li>
</ul>
 <div class='newInnerHTML' title='java' style='display: none;'>Java</div><div class='toggleable_div label_java' style='display: none;'><ul>
<li>The tutorial code's is shown lines below. You can also download it from <a href="https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/ImgTrans/canny_detector/CannyDetectorDemo.java">here</a> <div class="fragment"><div class="line"><span class="keyword">import</span> java.awt.BorderLayout;</div><div class="line"><span class="keyword">import</span> java.awt.Container;</div><div class="line"><span class="keyword">import</span> java.awt.Image;</div><div class="line"></div><div class="line"><span class="keyword">import</span> javax.swing.BoxLayout;</div><div class="line"><span class="keyword">import</span> javax.swing.ImageIcon;</div><div class="line"><span class="keyword">import</span> javax.swing.JFrame;</div><div class="line"><span class="keyword">import</span> javax.swing.JLabel;</div><div class="line"><span class="keyword">import</span> javax.swing.JPanel;</div><div class="line"><span class="keyword">import</span> javax.swing.JSlider;</div><div class="line"><span class="keyword">import</span> javax.swing.event.ChangeEvent;</div><div class="line"><span class="keyword">import</span> javax.swing.event.ChangeListener;</div><div class="line"></div><div class="line"><span class="keyword">import</span> org.opencv.core.Core;</div><div class="line"><span class="keyword">import</span> org.opencv.core.CvType;</div><div class="line"><span class="keyword">import</span> org.opencv.core.Mat;</div><div class="line"><span class="keyword">import</span> org.opencv.core.Scalar;</div><div class="line"><span class="keyword">import</span> org.opencv.core.Size;</div><div class="line"><span class="keyword">import</span> org.opencv.highgui.HighGui;</div><div class="line"><span class="keyword">import</span> org.opencv.imgcodecs.Imgcodecs;</div><div class="line"><span class="keyword">import</span> org.opencv.imgproc.Imgproc;</div><div class="line"></div><div class="line"><span class="keyword">public</span> <span class="keyword">class </span>CannyDetectorDemo {</div><div class="line">    <span class="keyword">private</span> <span class="keyword">static</span> <span class="keyword">final</span> <span class="keywordtype">int</span> MAX_LOW_THRESHOLD = 100;</div><div class="line">    <span class="keyword">private</span> <span class="keyword">static</span> <span class="keyword">final</span> <span class="keywordtype">int</span> RATIO = 3;</div><div class="line">    <span class="keyword">private</span> <span class="keyword">static</span> <span class="keyword">final</span> <span class="keywordtype">int</span> KERNEL_SIZE = 3;</div><div class="line">    <span class="keyword">private</span> <span class="keyword">static</span> <span class="keyword">final</span> <a class="code" href="../../dc/d84/group__core__basic.html#ga346f563897249351a34549137c8532a0">Size</a> BLUR_SIZE = <span class="keyword">new</span> <a class="code" href="../../dc/d84/group__core__basic.html#ga346f563897249351a34549137c8532a0">Size</a>(3,3);</div><div class="line">    <span class="keyword">private</span> <span class="keywordtype">int</span> lowThresh = 0;</div><div class="line">    <span class="keyword">private</span> Mat src;</div><div class="line">    <span class="keyword">private</span> Mat srcBlur = <span class="keyword">new</span> Mat();</div><div class="line">    <span class="keyword">private</span> Mat detectedEdges = <span class="keyword">new</span> Mat();</div><div class="line">    <span class="keyword">private</span> Mat dst = <span class="keyword">new</span> Mat();</div><div class="line">    <span class="keyword">private</span> JFrame frame;</div><div class="line">    <span class="keyword">private</span> JLabel imgLabel;</div><div class="line"></div><div class="line">    <span class="keyword">public</span> CannyDetectorDemo(<a class="code" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a>[] args) {</div><div class="line">        <a class="code" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a> imagePath = args.length &gt; 0 ? args[0] : <span class="stringliteral">&quot;../data/fruits.jpg&quot;</span>;</div><div class="line">        src = Imgcodecs.imread(imagePath);</div><div class="line">        <span class="keywordflow">if</span> (src.empty()) {</div><div class="line">            System.out.println(<span class="stringliteral">&quot;Empty image: &quot;</span> + imagePath);</div><div class="line">            System.exit(0);</div><div class="line">        }</div><div class="line"></div><div class="line">        <span class="comment">// Create and set up the window.</span></div><div class="line">        frame = <span class="keyword">new</span> JFrame(<span class="stringliteral">&quot;Edge Map (Canny detector demo)&quot;</span>);</div><div class="line">        frame.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);</div><div class="line">        <span class="comment">// Set up the content pane.</span></div><div class="line">        Image img = HighGui.toBufferedImage(src);</div><div class="line">        addComponentsToPane(frame.getContentPane(), img);</div><div class="line">        <span class="comment">// Use the content pane&#39;s default BorderLayout. No need for</span></div><div class="line">        <span class="comment">// setLayout(new BorderLayout());</span></div><div class="line">        <span class="comment">// Display the window.</span></div><div class="line">        frame.pack();</div><div class="line">        frame.setVisible(<span class="keyword">true</span>);</div><div class="line">    }</div><div class="line"></div><div class="line">    <span class="keyword">private</span> <span class="keywordtype">void</span> addComponentsToPane(Container pane, Image img) {</div><div class="line">        <span class="keywordflow">if</span> (!(pane.getLayout() instanceof BorderLayout)) {</div><div class="line">            pane.add(<span class="keyword">new</span> JLabel(<span class="stringliteral">&quot;Container doesn&#39;t use BorderLayout!&quot;</span>));</div><div class="line">            <span class="keywordflow">return</span>;</div><div class="line">        }</div><div class="line"></div><div class="line">        JPanel sliderPanel = <span class="keyword">new</span> JPanel();</div><div class="line">        sliderPanel.setLayout(<span class="keyword">new</span> BoxLayout(sliderPanel, BoxLayout.PAGE_AXIS));</div><div class="line"></div><div class="line">        sliderPanel.add(<span class="keyword">new</span> JLabel(<span class="stringliteral">&quot;Min Threshold:&quot;</span>));</div><div class="line">        JSlider slider = <span class="keyword">new</span> JSlider(0, MAX_LOW_THRESHOLD, 0);</div><div class="line">        slider.setMajorTickSpacing(10);</div><div class="line">        slider.setMinorTickSpacing(5);</div><div class="line">        slider.setPaintTicks(<span class="keyword">true</span>);</div><div class="line">        slider.setPaintLabels(<span class="keyword">true</span>);</div><div class="line">        slider.addChangeListener(<span class="keyword">new</span> ChangeListener() {</div><div class="line">            @Override</div><div class="line">            <span class="keyword">public</span> <span class="keywordtype">void</span> stateChanged(ChangeEvent e) {</div><div class="line">                JSlider source = (JSlider) e.getSource();</div><div class="line">                lowThresh = source.getValue();</div><div class="line">                update();</div><div class="line">            }</div><div class="line">        });</div><div class="line">        sliderPanel.add(slider);</div><div class="line"></div><div class="line">        pane.add(sliderPanel, BorderLayout.PAGE_START);</div><div class="line">        imgLabel = <span class="keyword">new</span> JLabel(<span class="keyword">new</span> ImageIcon(img));</div><div class="line">        pane.add(imgLabel, BorderLayout.CENTER);</div><div class="line">    }</div><div class="line"></div><div class="line">    <span class="keyword">private</span> <span class="keywordtype">void</span> update() {</div><div class="line">        Imgproc.blur(src, srcBlur, BLUR_SIZE);</div><div class="line">        Imgproc.Canny(srcBlur, detectedEdges, lowThresh, lowThresh * RATIO, KERNEL_SIZE, <span class="keyword">false</span>);</div><div class="line">        dst = <span class="keyword">new</span> Mat(src.size(), CvType.CV_8UC3, <a class="code" href="../../dc/d84/group__core__basic.html#ga599fe92e910c027be274233eccad7beb">Scalar</a>.<a class="code" href="../../d1/da0/classcv_1_1Scalar__.html#ac1509a4b8454fe7fe29db069e13a2e6f">all</a>(0));</div><div class="line">        src.copyTo(dst, detectedEdges);</div><div class="line">        Image img = HighGui.toBufferedImage(dst);</div><div class="line">        imgLabel.setIcon(<span class="keyword">new</span> ImageIcon(img));</div><div class="line">        frame.repaint();</div><div class="line">    }</div><div class="line"></div><div class="line">    <span class="keyword">public</span> <span class="keyword">static</span> <span class="keywordtype">void</span> main(<a class="code" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a>[] args) {</div><div class="line">        <span class="comment">// Load the native OpenCV library</span></div><div class="line">        System.loadLibrary(Core.NATIVE_LIBRARY_NAME);</div><div class="line"></div><div class="line">        <span class="comment">// Schedule a job for the event dispatch thread:</span></div><div class="line">        <span class="comment">// creating and showing this application&#39;s GUI.</span></div><div class="line">        javax.swing.SwingUtilities.invokeLater(<span class="keyword">new</span> Runnable() {</div><div class="line">            @Override</div><div class="line">            <span class="keyword">public</span> <span class="keywordtype">void</span> run() {</div><div class="line">                <span class="keyword">new</span> CannyDetectorDemo(args);</div><div class="line">            }</div><div class="line">        });</div><div class="line">    }</div><div class="line">}</div></div><!-- fragment -->  </div> </li>
</ul>
 <div class='newInnerHTML' title='python' style='display: none;'>Python</div><div class='toggleable_div label_python' style='display: none;'><ul>
<li>The tutorial code's is shown lines below. You can also download it from <a href="https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/ImgTrans/canny_detector/CannyDetector_Demo.py">here</a> <div class="fragment"><div class="line"><span class="keyword">from</span> __future__ <span class="keyword">import</span> print_function</div><div class="line"><span class="keyword">import</span> cv2 <span class="keyword">as</span> cv</div><div class="line"><span class="keyword">import</span> argparse</div><div class="line"></div><div class="line">max_lowThreshold = 100</div><div class="line">window_name = <span class="stringliteral">&#39;Edge Map&#39;</span></div><div class="line">title_trackbar = <span class="stringliteral">&#39;Min Threshold:&#39;</span></div><div class="line">ratio = 3</div><div class="line">kernel_size = 3</div><div class="line"></div><div class="line"><span class="keyword">def </span>CannyThreshold(val):</div><div class="line">    low_threshold = val</div><div class="line">    img_blur = <a class="code" href="../../d4/d86/group__imgproc__filter.html#ga8c45db9afe636703801b0b2e440fce37">cv.blur</a>(src_gray, (3,3))</div><div class="line">    detected_edges = <a class="code" href="../../dd/d1a/group__imgproc__feature.html#ga2a671611e104c093843d7b7fc46d24af">cv.Canny</a>(img_blur, low_threshold, low_threshold*ratio, kernel_size)</div><div class="line">    mask = detected_edges != 0</div><div class="line">    dst = src * (mask[:,:,<span class="keywordtype">None</span>].astype(src.dtype))</div><div class="line">    <a class="code" href="../../df/d24/group__highgui__opengl.html#gaae7e90aa3415c68dba22a5ff2cefc25d">cv.imshow</a>(window_name, dst)</div><div class="line"></div><div class="line">parser = argparse.ArgumentParser(description=<span class="stringliteral">&#39;Code for Canny Edge Detector tutorial.&#39;</span>)</div><div class="line">parser.add_argument(<span class="stringliteral">&#39;--input&#39;</span>, help=<span class="stringliteral">&#39;Path to input image.&#39;</span>, default=<span class="stringliteral">&#39;fruits.jpg&#39;</span>)</div><div class="line">args = parser.parse_args()</div><div class="line"></div><div class="line">src = <a class="code" href="../../d4/da8/group__imgcodecs.html#ga288b8b3da0892bd651fce07b3bbd3a56">cv.imread</a>(<a class="code" href="../../d6/dba/group__core__utils__samples.html#ga3a33b00033b46c698ff6340d95569c13">cv.samples.findFile</a>(args.input))</div><div class="line"><span class="keywordflow">if</span> src <span class="keywordflow">is</span> <span class="keywordtype">None</span>:</div><div class="line">    <a class="code" href="../../df/d57/namespacecv_1_1dnn.html#a701210a0203f2786cbfd04b2bd56da47">print</a>(<span class="stringliteral">&#39;Could not open or find the image: &#39;</span>, args.input)</div><div class="line">    exit(0)</div><div class="line"></div><div class="line">src_gray = <a class="code" href="../../d8/d01/group__imgproc__color__conversions.html#ga397ae87e1288a81d2363b61574eb8cab">cv.cvtColor</a>(src, cv.COLOR_BGR2GRAY)</div><div class="line"></div><div class="line"><a class="code" href="../../d7/dfc/group__highgui.html#ga5afdf8410934fd099df85c75b2e0888b">cv.namedWindow</a>(window_name)</div><div class="line"><a class="code" href="../../d7/dfc/group__highgui.html#gaf78d2155d30b728fc413803745b67a9b">cv.createTrackbar</a>(title_trackbar, window_name , 0, max_lowThreshold, CannyThreshold)</div><div class="line"></div><div class="line">CannyThreshold(0)</div><div class="line"><a class="code" href="../../d7/dfc/group__highgui.html#ga5628525ad33f52eab17feebcfba38bd7">cv.waitKey</a>()</div></div><!-- fragment -->  </div> </li>
<li><b>What does this program do?</b><ul>
<li>Asks the user to enter a numerical value to set the lower threshold for our <em>Canny Edge Detector</em> (by means of a Trackbar).</li>
<li>Applies the <em>Canny Detector</em> and generates a <b>mask</b> (bright lines representing the edges on a black background).</li>
<li>Applies the mask obtained on the original image and display it in a window.</li>
</ul>
</li>
</ul>
<h2>Explanation (C++ code) </h2>
<ol type="1">
<li>Create some needed variables: <div class="fragment"><div class="line">Mat src, src_gray;</div><div class="line">Mat dst, detected_edges;</div><div class="line"></div><div class="line"><span class="keywordtype">int</span> lowThreshold = 0;</div><div class="line"><span class="keyword">const</span> <span class="keywordtype">int</span> max_lowThreshold = 100;</div><div class="line"><span class="keyword">const</span> <span class="keywordtype">int</span> ratio = 3;</div><div class="line"><span class="keyword">const</span> <span class="keywordtype">int</span> kernel_size = 3;</div><div class="line"><span class="keyword">const</span> <span class="keywordtype">char</span>* window_name = <span class="stringliteral">&quot;Edge Map&quot;</span>;</div></div><!-- fragment --> Note the following:<ol type="a">
<li>We establish a ratio of lower:upper threshold of 3:1 (with the variable <em>ratio</em>).</li>
<li>We set the kernel size of \(3\) (for the Sobel operations to be performed internally by the Canny function).</li>
<li>We set a maximum value for the lower Threshold of \(100\).</li>
</ol>
</li>
<li>Loads the source image: <div class="fragment"><div class="line">  CommandLineParser parser( argc, argv, <span class="stringliteral">&quot;{@input | fruits.jpg | input image}&quot;</span> );</div><div class="line">  src = <a class="code" href="../../d4/da8/group__imgcodecs.html#ga288b8b3da0892bd651fce07b3bbd3a56">imread</a>( <a class="code" href="../../d6/dba/group__core__utils__samples.html#ga3a33b00033b46c698ff6340d95569c13">samples::findFile</a>( parser.get&lt;<a class="code" href="../../dc/d84/group__core__basic.html#ga1f6634802eeadfd7245bc75cf3e216c2">String</a>&gt;( <span class="stringliteral">&quot;@input&quot;</span> ) ), <a class="code" href="../../d8/d6a/group__imgcodecs__flags.html#gga61d9b0126a3e57d9277ac48327799c80af660544735200cbe942eea09232eb822">IMREAD_COLOR</a> ); <span class="comment">// Load an image</span></div><div class="line"></div><div class="line">  <span class="keywordflow">if</span>( src.empty() )</div><div class="line">  {</div><div class="line">    std::cout &lt;&lt; <span class="stringliteral">&quot;Could not open or find the image!\n&quot;</span> &lt;&lt; std::endl;</div><div class="line">    std::cout &lt;&lt; <span class="stringliteral">&quot;Usage: &quot;</span> &lt;&lt; argv[0] &lt;&lt; <span class="stringliteral">&quot; &lt;Input image&gt;&quot;</span> &lt;&lt; std::endl;</div><div class="line">    <span class="keywordflow">return</span> -1;</div><div class="line">  }</div></div><!-- fragment --></li>
<li>Create a matrix of the same type and size of <em>src</em> (to be <em>dst</em>): <div class="fragment"><div class="line">  dst.create( src.size(), src.type() );</div></div><!-- fragment --></li>
<li>Convert the image to grayscale (using the function <a class="el" href="../../d8/d01/group__imgproc__color__conversions.html#ga397ae87e1288a81d2363b61574eb8cab">cv::cvtColor</a> ): <div class="fragment"><div class="line">  <a class="code" href="../../d8/d01/group__imgproc__color__conversions.html#ga397ae87e1288a81d2363b61574eb8cab">cvtColor</a>( src, src_gray, <a class="code" href="../../d8/d01/group__imgproc__color__conversions.html#gga4e0972be5de079fed4e3a10e24ef5ef0a353a4b8db9040165db4dacb5bcefb6ea">COLOR_BGR2GRAY</a> );</div></div><!-- fragment --></li>
<li>Create a window to display the results: <div class="fragment"><div class="line">  <a class="code" href="../../d7/dfc/group__highgui.html#ga5afdf8410934fd099df85c75b2e0888b">namedWindow</a>( window_name, <a class="code" href="../../d0/d90/group__highgui__window__flags.html#ggabf7d2c5625bc59ac130287f925557ac3acf621ace7a54954cbac01df27e47228f">WINDOW_AUTOSIZE</a> );</div></div><!-- fragment --></li>
<li>Create a Trackbar for the user to enter the lower threshold for our Canny detector: <div class="fragment"><div class="line">  <a class="code" href="../../d7/dfc/group__highgui.html#gaf78d2155d30b728fc413803745b67a9b">createTrackbar</a>( <span class="stringliteral">&quot;Min Threshold:&quot;</span>, window_name, &amp;lowThreshold, max_lowThreshold, CannyThreshold );</div></div><!-- fragment --> Observe the following:<ol type="a">
<li>The variable to be controlled by the Trackbar is <em>lowThreshold</em> with a limit of <em>max_lowThreshold</em> (which we set to 100 previously)</li>
<li>Each time the Trackbar registers an action, the callback function <em>CannyThreshold</em> will be invoked.</li>
</ol>
</li>
<li>Let's check the <em>CannyThreshold</em> function, step by step:<ol type="a">
<li>First, we blur the image with a filter of kernel size 3: <div class="fragment"><div class="line">    <a class="code" href="../../d4/d86/group__imgproc__filter.html#ga8c45db9afe636703801b0b2e440fce37">blur</a>( src_gray, detected_edges, <a class="code" href="../../dc/d84/group__core__basic.html#ga346f563897249351a34549137c8532a0">Size</a>(3,3) );</div></div><!-- fragment --></li>
<li>Second, we apply the OpenCV function <a class="el" href="../../dd/d1a/group__imgproc__feature.html#ga04723e007ed888ddf11d9ba04e2232de">cv::Canny</a> : <div class="fragment"><div class="line">    <a class="code" href="../../dd/d1a/group__imgproc__feature.html#ga04723e007ed888ddf11d9ba04e2232de">Canny</a>( detected_edges, detected_edges, lowThreshold, lowThreshold*ratio, kernel_size );</div></div><!-- fragment --> where the arguments are:<ul>
<li><em>detected_edges</em>: Source image, grayscale</li>
<li><em>detected_edges</em>: Output of the detector (can be the same as the input)</li>
<li><em>lowThreshold</em>: The value entered by the user moving the Trackbar</li>
<li><em>highThreshold</em>: Set in the program as three times the lower threshold (following Canny's recommendation)</li>
<li><em>kernel_size</em>: We defined it to be 3 (the size of the Sobel kernel to be used internally)</li>
</ul>
</li>
</ol>
</li>
<li>We fill a <em>dst</em> image with zeros (meaning the image is completely black). <div class="fragment"><div class="line">    dst = Scalar::all(0);</div></div><!-- fragment --></li>
<li>Finally, we will use the function <a class="el" href="../../d3/d63/classcv_1_1Mat.html#a33fd5d125b4c302b0c9aa86980791a77">cv::Mat::copyTo</a> to map only the areas of the image that are identified as edges (on a black background). <a class="el" href="../../d3/d63/classcv_1_1Mat.html#a33fd5d125b4c302b0c9aa86980791a77">cv::Mat::copyTo</a> copy the <em>src</em> image onto <em>dst</em>. However, it will only copy the pixels in the locations where they have non-zero values. Since the output of the Canny detector is the edge contours on a black background, the resulting <em>dst</em> will be black in all the area but the detected edges. <div class="fragment"><div class="line">    src.copyTo( dst, detected_edges);</div></div><!-- fragment --></li>
<li>We display our result: <div class="fragment"><div class="line">    <a class="code" href="../../d7/dfc/group__highgui.html#ga453d42fe4cb60e5723281a89973ee563">imshow</a>( window_name, dst );</div></div><!-- fragment --> <h2>Result </h2>
</li>
</ol>
<ul>
<li><p class="startli">After compiling the code above, we can run it giving as argument the path to an image. For example, using as an input the following image:</p>
<div class="image">
<img src="../../Canny_Detector_Tutorial_Original_Image.jpg" alt="Canny_Detector_Tutorial_Original_Image.jpg"/>
</div>
</li>
<li><p class="startli">Moving the slider, trying different threshold, we obtain the following result:</p>
<div class="image">
<img src="../../Canny_Detector_Tutorial_Result.jpg" alt="Canny_Detector_Tutorial_Result.jpg"/>
</div>
</li>
<li>Notice how the image is superposed to the black background on the edge regions. </li>
</ul>
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